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NVIDIA 2D Thread Scheduler Fixed #421
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Related issue: #356 |
...s/opencl/src/main/java/uk/ac/manchester/tornado/drivers/opencl/TornadoPlatformInterface.java
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private long[] calculateEffectiveMaxWorkItemSizes(TaskMetaData metaData) { | ||
long[] intermediates = new long[] { 1, 1, 1 }; |
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any particular reasoning for this particular name of the array? Shouldn't this reflect the max work items?
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This is to calculate the local Work Group. We initialize it to one and then fill with the dimensions used.
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yes, but the name is intermediates
? can we make it more specific?
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Yes, I agree. I just did a refactoring of this method
…drivers/opencl/TornadoPlatformInterface.java Co-authored-by: Thanos Stratikopoulos <34061419+stratika@users.noreply.github.com>
I guess for older driver versions, we will not see any difference, right? I tried it with |
…uler' into feat/nvidia/scheduler
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LGTM
Improvements ~~~~~~~~~~~~~~~~~~ - beehive-lab#402 <beehive-lab#402>: Support for TornadoNativeArrays from FFI buffers. - beehive-lab#403 <beehive-lab#403>: Clean-up and refactoring for the code analysis of the loop-interchange. - beehive-lab#405 <beehive-lab#405>: Disable Loop-Interchange for CPU offloading.. - beehive-lab#407 <beehive-lab#407>: Debugging OpenCL Kernels builds improved. - beehive-lab#410 <beehive-lab#410>: CPU block scheduler disabled by default and option to switch between different thread-schedulers added. - beehive-lab#418 <beehive-lab#418>: TornadoOptions and TornadoLogger improved. - beehive-lab#423 <beehive-lab#423>: MxM using ns instead of ms to report performance. - beehive-lab#425 <beehive-lab#425>: Vector types for ``Float<Width>`` and ``Int<Width>`` supported. - beehive-lab#429 <beehive-lab#429>: Documentation of the installation process updated and improved. - beehive-lab#432 <beehive-lab#432>: Support for SPIR-V code generation and dispatcher using the TornadoVM OpenCL runtime. Compatibility ~~~~~~~~~~~~~~~~~~ - beehive-lab#409 <beehive-lab#409>: Guidelines to build the documentation. - beehive-lab#411 <beehive-lab#411>: Windows installer improved. - beehive-lab#412 <beehive-lab#412>: Python installer improved to check download all Python dependencies before the main installer. - beehive-lab#413 <beehive-lab#413>: Improved documentation for installing all configurations of backends and OS. - beehive-lab#424 <beehive-lab#424>: Use Generic GPU Scheduler for some older NVIDIA Drivers for the OpenCL runtime. - beehive-lab#430 <beehive-lab#430>: Improved the installer by checking that the TornadoVM environment is loaded upfront. Bug Fixes ~~~~~~~~~~~~~~~~~~ - beehive-lab#400 <beehive-lab#400>: Fix batch computation when the global thread indexes are used to compute the outputs. - beehive-lab#414 <beehive-lab#414>: Recover Test-Field unit-tests using Panama types. - beehive-lab#415 <beehive-lab#415>: Check style errors fixed. - beehive-lab#416 <beehive-lab#416>: FPGA execution with multiple tasks in a task-graph fixed. - beehive-lab#417 <beehive-lab#417>: Lazy-copy out fixed for Java fields. - beehive-lab#420 <beehive-lab#420>: Fix Mandelbrot example. - beehive-lab#421 <beehive-lab#421>: OpenCL 2D thread-scheduler fixed for NVIDIA GPUs. - beehive-lab#422 <beehive-lab#422>: Compilation for NVIDIA Jetson Nano fixed. - beehive-lab#426 <beehive-lab#426>: Fix Logger for all backends. - beehive-lab#428 <beehive-lab#428>: Math cos/sin operations supported for vector types. - beehive-lab#431 <beehive-lab#431>: Jenkins files fixed.
Description
This patch provides a new Thread Scheduler for NVIDIA GPUs.
Problem description
The problem is that, when using the latest NVIDIA Drivers (e.g., 550.76), the thread block is set to 32x32 for 2D kernels. This block size seems to be illegal only when using the latest NVIDIA drivers. This patch provides a custom NVIDIA scheduler to fix this. Performance over the default scheduler increases ~300GFLOPs on my RTX 3070 GPU for the canonical matrix multiplications with this patch.
Backend/s tested
Mark the backends affected by this PR.
OS tested
Mark the OS where this PR is tested.
Did you check on FPGAs?
If it is applicable, check your changes on FPGAs.
How to test the new patch?